Search (25 results, page 1 of 2)

  • × theme_ss:"Formale Begriffsanalyse"
  1. Priss, U.; Jacob, E.: Utilizing faceted structures for information systems design (1999) 0.03
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    Abstract
    The writers show that a faceted navigation structure makes web sites easier to use. They begin by analyzing the web sites of three library and information science faculties, and seeing if the sites easily provide the answers to five specific questions, e.g., how the school ranks in national evaluations. (It is worth noting that the web site of the Faculty of Information Studies and the University of Toronto, where this bibliography is being written, would fail on four of the five questions.) Using examples from LIS web site content, they show how facets can be related and constructed, and use concept diagrams for illustration. They briefly discuss constraints necessary when joining facets: for example, enrolled students can be full- or part-time, but prospective and alumni students cannot. It should not be possible to construct terms such as "part-time alumni" (see Yannis Tzitzikas et al, below in Background). They conclude that a faceted approach is best for web site navigation, because it can clearly show where the user is in the site, what the related pages are, and how to get to them. There is a short discussion of user interfaces, and the diagrams in the paper will be of interest to anyone making a facet-based web site. This paper is clearly written, informative, and thought-provoking. Uta Priss's web site lists her other publications, many of which are related and some of which are online: http://www.upriss.org.uk/top/research.html.
  2. Priss, U.: Faceted information representation (2000) 0.01
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    Abstract
    This paper presents an abstract formalization of the notion of "facets". Facets are relational structures of units, relations and other facets selected for a certain purpose. Facets can be used to structure large knowledge representation systems into a hierarchical arrangement of consistent and independent subsystems (facets) that facilitate flexibility and combinations of different viewpoints or aspects. This paper describes the basic notions, facet characteristics and construction mechanisms. It then explicates the theory in an example of a faceted information retrieval system (FaIR)
    Date
    22. 1.2016 17:47:06
  3. Priss, U.: Faceted knowledge representation (1999) 0.01
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    Abstract
    Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.
    Date
    22. 1.2016 17:30:31
  4. Priss, U.: Formal concept analysis in information science (2006) 0.01
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    Date
    13. 7.2008 19:29:59
  5. Wille, R.: Line diagrams of hierarchical concept systems (1984) 0.01
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  6. Wille, R.: Concept lattices and conceptual knowledge systems (1992) 0.01
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  7. Scheich, P.; Skorsky, M.; Vogt, F.; Wachter, C.; Wille, R.: Conceptual data systems (1992) 0.01
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  8. Priss, U.; Old, L.J.: Concept neighbourhoods in knowledge organisation systems (2010) 0.01
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    Abstract
    This paper discusses the application of concept neighbourhoods (in the sense of formal concept analysis) to knowledge organisation systems. Examples are provided using Roget's Thesaurus, WordNet and Wikipedia categories.
    Source
    Paradigms and conceptual systems in knowledge organization: Proceedings of the Eleventh International ISKO Conference, 23-26 February 2010 Rome, Italy. Edited by Claudio Gnoli and Fulvio Mazzocchi
  9. Prediger, S.: Kontextuelle Urteilslogik mit Begriffsgraphen : Ein Beitrag zur Restrukturierung der mathematischen Logik (1998) 0.00
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    Date
    26. 2.2008 15:58:22
  10. Scheich, P.; Skorsky, M.; Vogt, F.; Wachter, C.; Wille, R.: Conceptual data systems (1993) 0.00
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  11. Rusch, A.; Wille, R.: Knowledge spaces and formal concept analysis (1996) 0.00
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    Source
    Data analysis and information systems, statistical and conceptual approaches: Proceedings of the 19th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Basel, March 8-10, 1995. Ed.: H.-H. Bock u. W. Polasek
  12. Eschenfelder, D.; Kollewe, W.; Skorsky, M.; Wille, R.: ¬Ein Erkundungssystem zum Baurecht : Methoden der Entwicklung eines TOSCANA-Systems (2000) 0.00
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  13. Vogt, F.; Wille, R.: TOSCANA - a graphical tool for analyzing and exploring data (1995) 0.00
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    Source
    Knowledge organization. 22(1995) no.2, S.78-81
  14. Reinartz, T.P.; Zickwolff, M.: ¬Two conceptual approaches to acquire human expert knowledge in a complex real world domain (1996) 0.00
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    Source
    Data analysis and information systems, statistical and conceptual approaches: Proceedings of the 19th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Basel, March 8-10, 1995. Ed.: H.-H. Bock u. W. Polasek
  15. Groh, B.; Strahringer, S.; Wille, R.: TOSCANA-systems based on thesauri (1998) 0.00
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  16. Luksch, P.; Wille, R.: ¬A mathematical model for conceptual knowledge systems (1991) 0.00
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    Abstract
    Objects, attributes, and concepts are basic notations of conceptual knowledge; they are linked by the following four basic relations: an object has an attribute, an object belongs to a concept, an attribute abstracts from a concept, and a concept is a subconcept of another concept. These structural elements are well mathematized in formal concept analysis. Therefore, conceptual knowledge systems can be mathematically modelled in the frame of formal concept analysis. How such modelling may be performed is indicated by an example of a conceptual knowledge system. The formal definition of the model finally clarifies in which ways representation, inference, acquisition, and communication of conceptual knowledge can be mathematically treated
  17. De Maio, C.; Fenza, G.; Loia, V.; Senatore, S.: Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis (2012) 0.00
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    Abstract
    In recent years, knowledge structuring is assuming important roles in several real world applications such as decision support, cooperative problem solving, e-commerce, Semantic Web and, even in planning systems. Ontologies play an important role in supporting automated processes to access information and are at the core of new strategies for the development of knowledge-based systems. Yet, developing an ontology is a time-consuming task which often needs an accurate domain expertise to tackle structural and logical difficulties in the definition of concepts as well as conceivable relationships. This work presents an ontology-based retrieval approach, that supports data organization and visualization and provides a friendly navigation model. It exploits the fuzzy extension of the Formal Concept Analysis theory to elicit conceptualizations from datasets and generate a hierarchy-based representation of extracted knowledge. An intuitive graphical interface provides a multi-facets view of the built ontology. Through a transparent query-based retrieval, final users navigate across concepts, relations and population.
  18. Neuss, C.; Kent, R.E.: Conceptual analysis of resource meta-information (1995) 0.00
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    Source
    Computer networks and ISDN systems. 27(1995) no.6, S.973-984
  19. Priss, U.: Comparing classification systems using facets (2000) 0.00
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  20. Ganter, B.; Wille, R.: Formal concept analysis : mathematical foundations (1998) 0.00
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    Abstract
    This is the first textbook on formal concept analysis. It gives a systematic presentation of the mathematical foundations and their relation to applications in computer science, especially data analysis and knowledge processing. Above all, it presents graphical methods for representing conceptual systems that have proved themselves in communicating knowledge. Theory and graphical representation are thus closely coupled together. The mathematical foundations are treated thouroughly and illuminated by means of numerous examples. Since computers are being used ever more widely for knowledge processing, formal methods for conceptual analysis are gaining in importance. This book makes the basic theory for such methods accessible in a compact form